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20022019
most citedA Comparative Study on Transformer vs RNN in Speech Applications

788 citations

Showing 2018Show all

5 papers · 1 filter

stat.ML2018★ 6 cited

Variational Autoencoder with Implicit Optimal Priors

Hiroshi Takahashi, Tomoharu Iwata, Yuki Yamanaka +2

The variational autoencoder (VAE) is a powerful generative model that can estimate the probability of a data point by using latent variables. In the VAE, the posterior of the laten…

cs.LG2018★ 37 cited

Interpretable Adversarial Perturbation in Input Embedding Space for Text

Motoki Sato, Jun Suzuki, Hiroyuki Shindo +1

Following great success in the image processing field, the idea of adversarial training has been applied to tasks in the natural language processing (NLP) field. One promising appr…

cs.DS2018★ 1 cited

On Maximization of Weakly Modular Functions: Guarantees of Multi-stage Algorithms, Tractability, and Hardness

Shinsaku Sakaue

Maximization of {\it non-submodular} functions appears in various scenarios, and many previous works studied it based on some measures that quantify the closeness to being submodul…

cs.CL2018★ 74 cited

ESPnet: End-to-End Speech Processing Toolkit

Shinji Watanabe, Takaaki Hori, Shigeki Karita +9

This paper introduces a new open source platform for end-to-end speech processing named ESPnet. ESPnet mainly focuses on end-to-end automatic speech recognition (ASR), and adopts w…

stat.ML2018★ 77 cited

Differentiable Dynamic Programming for Structured Prediction and Attention

Arthur Mensch, Mathieu Blondel

Dynamic programming (DP) solves a variety of structured combinatorial problems by iteratively breaking them down into smaller subproblems. In spite of their versatility, DP algorit…